Project Objective

This project's goal is to analyze which free/open hotspots and road sections are located. As a result, we are able to pinpoint the areas and routes with the best internet infrastructure for testing new services. Koln will serve as my use case. It will be simpler to choose the locations for new services, such as speed monitoring, traffic light smart atomation, or any IOT application related to smart cities, if you have access to the road sections with the appropriate internet infrastructure. This site will make it feasible to test new technologies without having to worry about building the necessary infrastructure.

Data science Question :

Which intersections in Kolen have access to a hotspot WIFI?

Import libraries

Load Data

Our Dataset consists of two tables : | Table name | Short discription | | -------- | ------- | | Hotspots in Köln | List of urban hotspots in Köln. In addition to some information regarding this hotspots like the geometrical location , the house number and street name. | | Road sections Köln | The Köln street directory provides an overview of all applicable street names , addresses , geometry paths and house numbers in each road section |

Visulaize Data

To get an overview of the Dataset, i will visualize an overview of our tables. This overview contain the most important infromation in each table

Data preparation

We need to prepare the data before we proceed with our solutions to the data science challenge.

In our database, the street names serve as the primary key. Unfortunately, the tables don't have standardized street names; for instance, they may finish in XYZ str, XYZ strasse, or other variations. Due to this, merging the two tables and processing the data to find a solution is challenging.

So , the steps of data preparation :

Algorithms and solution

First solution :

We filter the road section that has house number that directly have a hotspot

Seconed solution :

we filter the road section that has house number that in a range of X meter around the intersection and has a hotspot.

Visualization of the solutions

First solution

Seconed Solution

Challenges and discussion

We are not running the data pipeline here becasue our data has been updated , but we use a local version which i have downloaded beforehand.